Remote intensive management to improve antiplatelet adherence in acute myocardial infarction: a secondary analysis of the randomized controlled IMMACULATE trial.

This study aim to investigate if remote intensive coaching for the first 6 months post-AMI will improve adherence to the twice-a-day antiplatelet medication, ticagrelor. Between July 8, 2015, to March 29, 2019, AMI patients were randomly assigned to remote intensive management (RIM) or standard care (SC). RIM participants underwent 6 months of weekly then two-weekly consultations to review medication side effects and medication adherence coaching by a centralized nurse practitioner team, whereas SC participants received usual cardiologist face-to-face consultations. Adherence to ticagrelor were determined using pill counting and serial platelet reactivity measurements for 12 months. A total of 149 (49.5%) of participants were randomized to RIM and 152 (50.5%) to SC. Adherence to ticagrelor was similar between RIM and SC group at 1 month (94.4 ± 0.7% vs. 93.6±14.7%, p = 0.537), 6 months (91.0±14.6% vs. 90.6±14.8%, p = 0.832) and 12 months (87.4±17.0% vs. 89.8±12.5%, p = 0.688). There was also no significant difference in platelet reactivity between the RIM and SC groups at 1 month (251AU*min [212-328] vs. 267AU*min [208-351], p = 0.399), 6 months (239AU*min [165-308] vs. 235AU*min [171-346], p = 0.610) and 12 months (249AU*min [177-432] vs. 259AU*min [182-360], p = 0.678). Sensitivity analysis did not demonstrate any association of ticagrelor adherence with bleeding events and major adverse cardiovascular events. RIM, comprising 6 months of intensive coaching by nurse practitioners, did not improve adherence to the twice-a-day medication ticagrelor compared with SC among patients with AMI. A gradual decline in ticagrelor adherence over 12 months was observed despite 6 months of intensive coaching.

Variability of the Plasma Lipidome and Subclinical Coronary Atherosclerosis.

OBJECTIVE: While the risk of acute coronary events has been associated with biological variability of circulating cholesterol, the association with variability of other atherogenic lipids remains less understood. We evaluated the longitudinal variability of 284 lipids and investigated their association with asymptomatic coronary atherosclerosis. Approach and Results: Circulating lipids were extracted from fasting blood samples of 83 community-sampled symptom-free participants (age 41-75 years), collected longitudinally over 6 months. Three types of coronary plaque volume (calcified, lipid-rich, and fibrotic) were quantified using computed tomography coronary angiogram. We first deconvoluted between-subject (CVg) and within-subject (CVw) lipid variabilities. We then tested whether the mean lipid abundance was different across groups categorized by Framingham risk score and plaques phenotypes (lipid-rich, fibrotic, and calcified). Finally, we investigated whether visit-to-visit variability of each lipid was associated with plaque burden. Most lipids (72.5%) exhibited higher CVg than CVw. Among the lipids (n=145) with 1.2-fold higher CVg than CVw, 26 species including glycerides and ceramides were significantly associated with Framingham risk score and the 3 plaque phenotypes (false discovery rate <0.05). In an exploratory analysis of person-specific visit-to-visit variability without multiple testing correction, high variability of 3 lysophospholipids (lysophosphatidylethanolamines 16:0, 18:0, and lysophosphatidylcholine O-18:1) was associated with lipid-rich and fibrotic (noncalcified) plaque volume while high variability of diacylglycerol 18:1_20:0, triacylglycerols 52:2, 52:3, and 52:4, ceramide d18:0/20:0, dihexosylceramide d18:1/16:0, and sphingomyelin 36:3 was associated with calcified plaque volume. CONCLUSIONS: High person-specific longitudinal variation of specific nonsterol lipids is associated with the burden of subclinical coronary atherosclerosis. Larger studies are needed to confirm these exploratory findings.

Simultaneous Polar Metabolite and N-Glycan Extraction Workflow for Joint-Omics Analysis: A Synergistic Approach for Novel Insights into Diseases.

Bioinformatics and machine learning tools have made it possible to integrate data across different -omics platforms for novel multiomic insights into diseases. To synergistically process -omics data in an integrative manner, analyte extractions for each -omics type need to be done on the same set of clinical samples. Therefore, we introduce a simultaneous dual extraction method for generating both metabolomic (polar metabolites only) and glycomic (protein-derived N-glycans only) profiles from one sample with good extraction efficiency and reproducibility. As proof of the usefulness of the extraction and joint-omics workflow, we applied it on platelet samples obtained from a cohort study comprising 66 coronary heart disease (CHD) patients and 34 matched healthy community-dwelling controls. The metabolomics and N-glycomics data sets were subjected to block partial least-squares-discriminant analysis (block-PLS-DA) based on sparse generalized canonical correlation analysis (CCA) for identifying relevant mechanistic interactions between metabolites and glycans. This joint-omics investigation revealed intermodulative roles that protein-bound carbohydrates or glycoproteins and amino acids have in metabolic pathways and through intermediate protein dysregulations. It also suggested a protective role of the glyco-redox network in CHD, demonstrating proof-of-principle for a joint-omics analysis in providing new insights into disease mechanisms, as enabled by a simultaneous polar metabolite and protein-derived N-glycan extraction workflow.

N-glycan profiles of acute myocardial infarction patients reveal potential biomarkers for diagnosis, severity assessment and treatment monitoring.

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Diagnostic challenges remain in this highly time-sensitive condition. Using capillary electrophoresis-laser-induced fluorescence, we analyzed the blood plasma N-glycan profile in a cohort study comprising 103 patients with AMI and 69 controls. Subsequently, the data generated was subjected to classification modeling to identify potential AMI biomarkers. An area under the Receiving Operating Characteristic curve (AUCROC) of 0.81 was obtained when discriminating AMI vs. non-MI patients. We postulate that the glycan profile involves a switch from a pro- to an anti-inflammatory state in the AMI pathophysiology. This was supported by significantly decreased levels in galactosylation, alongside increased levels in sialylation, afucosylation and GlcNAc bisection levels in the blood plasma of AMI patients. By substantiating the glycomics analysis with immunoglobulin G (IgG) protein measurements, robustness of the glycan-based classifiers was demonstrated. Changes in AMI-related IgG activities were also confirmed to be associated with alterations at the glycosylation level. Additionally, a glycan-biomarker panel derived from glycan features and current clinical biomarkers performed remarkably (AUCROC = 0.90, sensitivity = 0.579 at 5% false positive rate) when discriminating between patients with ST-segment elevation MI (n = 84) and non-ST-segment elevation MI (n = 19). Moreover, by applying the model trained using glycomics information, AMI and controls can still be discriminated at 1 and 6 months after baseline. Thus, glycomics biomarkers could potentially serve as a valuable complementary test to current diagnostic biomarkers. Additional research on their utility and associated biomechanisms via a large-scale study is recommended.

Temporal Changes in Extracellular Vesicle Hemostatic Protein Composition Predict Favourable Left Ventricular Remodeling after Acute Myocardial Infarction.

The subset of plasma extracellular vesicles (EVs) that coprecipitate with low-density lipoprotein (LDL-EVs) carry coagulation and fibrinolysis pathway proteins as cargo. We investigated the association between LDL-EV hemostatic/fibrinolysis protein ratios and post-acute myocardial infarction (post-AMI) left ventricular (LV) remodeling which precedes heart failure. Protein concentrations of von Willebrand factor (VWF), SerpinC1 and plasminogen were determined in LDL-EVs extracted from plasma samples obtained at baseline (within 72 h post-AMI), 1 month and 6 months post-AMI from 198 patients. Patients were categorized as exhibiting adverse (n = 98) or reverse (n = 100) LV remodeling based on changes in LV end-systolic volume (increased or decreased ≥15) over a 6-month period. Multiple level longitudinal data analysis with structural equation (ML-SEM) model was used to assess predictive value for LV remodeling independent of baseline differences. At baseline, protein levels of VWF, SerpinC1 and plasminogen in LDL-EVs did not differ between patients with adverse versus reverse LV remodeling. At 1 month post-AMI, protein levels of VWF and SerpinC1 decreased whilst plasminogen increased in patients with adverse LV remodeling. In contrast, VWF and plasminogen decreased whilst SerpinC1 remained unchanged in patients with reverse LV remodeling. Overall, compared with patients with adverse LV remodeling, higher levels of SerpinC1 and VWF but lower levels of plasminogen resulted in higher ratios of VWF:Plasminogen and SerpinC1:Plasminogen at both 1 month and 6 months post-AMI in patients with reverse LV remodeling. More importantly, ratios VWF:Plasminogen (AUC = 0.674) and SerpinC1:Plasminogen (AUC = 0.712) displayed markedly better prognostic power than NT-proBNP (AUC = 0.384), troponin-I (AUC = 0.467) or troponin-T (AUC = 0.389) (p < 0.001) to predict reverse LV remodeling post-AMI. Temporal changes in the ratios of coagulation to fibrinolysis pathway proteins in LDL-EVs outperform current standard plasma biomarkers in predicting post-AMI reverse LV remodeling. Our findings may provide clinical cues to uncover the cellular mechanisms underpinning post-AMI reverse LV remodeling.

Prioritizing Candidates of Post-Myocardial Infarction Heart Failure Using Plasma Proteomics and Single-Cell Transcriptomics.

BACKGROUND: Heart failure (HF) is the most common long-term complication of acute myocardial infarction (MI). Understanding plasma proteins associated with post-MI HF and their gene expression may identify new candidates for biomarker and drug target discovery. METHODS: We used aptamer-based affinity-capture plasma proteomics to measure 1305 plasma proteins at 1 month post-MI in a New Zealand cohort (CDCS [Coronary Disease Cohort Study]) including 181 patients post-MI who were subsequently hospitalized for HF in comparison with 250 patients post-MI who remained event free over a median follow-up of 4.9 years. We then correlated plasma proteins with left ventricular ejection fraction measured at 4 months post-MI and identified proteins potentially coregulated in post-MI HF using weighted gene co-expression network analysis. A Singapore cohort (IMMACULATE [Improving Outcomes in Myocardial Infarction through Reversal of Cardiac Remodelling]) of 223 patients post-MI, of which 33 patients were hospitalized for HF (median follow-up, 2.0 years), was used for further candidate enrichment of plasma proteins by using Fisher meta-analysis, resampling-based statistical testing, and machine learning. We then cross-referenced differentially expressed proteins with their differentially expressed genes from single-cell transcriptomes of nonmyocyte cardiac cells isolated from a murine MI model, and single-cell and single-nucleus transcriptomes of cardiac myocytes from murine HF models and human patients with HF. RESULTS: In the CDCS cohort, 212 differentially expressed plasma proteins were significantly associated with subsequent HF events. Of these, 96 correlated with left ventricular ejection fraction measured at 4 months post-MI. Weighted gene co-expression network analysis prioritized 63 of the 212 proteins that demonstrated significantly higher correlations among patients who developed post-MI HF in comparison with event-free controls (data set 1). Cross-cohort meta-analysis of the IMMACULATE cohort identified 36 plasma proteins associated with post-MI HF (data set 2), whereas single-cell transcriptomes identified 15 gene-protein candidates (data set 3). The majority of prioritized proteins were of matricellular origin. The 6 most highly enriched proteins that were common to all 3 data sets included well-established biomarkers of post-MI HF: N-terminal B-type natriuretic peptide and troponin T, and newly emergent biomarkers, angiopoietin-2, thrombospondin-2, latent transforming growth factor-ß binding protein-4, and follistatin-related protein-3, as well. CONCLUSIONS: Large-scale human plasma proteomics, cross-referenced to unbiased cardiac transcriptomics at single-cell resolution, prioritized protein candidates associated with post-MI HF for further mechanistic and clinical validation.

Shared reference materials harmonize lipidomics across MS-based detection platforms and laboratories.

Quantitative MS of human plasma lipids is a promising technology for translation into clinical applications. Current MS-based lipidomic methods rely on either direct infusion (DI) or chromatographic lipid separation methods (including reversed phase and hydrophilic interaction LC). However, the use of lipid markers in laboratory medicine is limited by the lack of reference values, largely because of considerable differences in the concentrations measured by different laboratories worldwide. These inconsistencies can be explained by the use of different sample preparation protocols, method-specific calibration procedures, and other experimental and data-reporting parameters, even when using identical starting materials. Here, we systematically investigated the roles of some of these variables in multiple approaches to lipid analysis of plasma samples from healthy adults by considering: 1) different sample introduction methods (separation vs. DI methods); 2) different MS instruments; and 3) between-laboratory differences in comparable analytical platforms. Each of these experimental variables resulted in different quantitative results, even with the inclusion of isotope-labeled internal standards for individual lipid classes. We demonstrated that appropriate normalization to commonly available reference samples (i.e., "shared references") can largely correct for these systematic method-specific quantitative biases. Thus, to harmonize data in the field of lipidomics, in-house long-term references should be complemented by a commonly available shared reference sample, such as NIST SRM 1950, in the case of human plasma.

Patients with acute and chronic coronary syndromes have elevated long-term thrombin generation.

Coronary artery disease is a leading cause of morbidity and mortality worldwide. Despite significant advances in revascularization strategies and antiplatelet therapy with aspirin and/or P2Y12 receptor antagonist, patients with acute coronary syndrome (ACS) continue to be at long-term risk of further cardiovascular events. Besides platelet activation, the role of thrombin generation (TG) in atherothrombotic complications is widely recognized. In this study, we hypothesized that there is an elevation of coagulation activation persists beyond 12 months in patients with ACS and chronic coronary syndrome (CCS) when compared with healthy controls. We measured TG profiles of patients within 72 h after percutaneous coronary intervention, at 6-month, 12-month and 24-month. Our results demonstrated that TG of patients with ACS (n = 114) and CCS (n = 40) were persistently elevated when compared to healthy individuals (n = 50) in peak thrombin (ACS 273.1 nM vs CCS 287.3 nM vs healthy 234.3 nM) and velocity index (ACS 110.2 nM/min vs CCS 111.0 nM/min vs healthy 72.9 nM/min) at 24-month of follow-up. Our results suggest a rationale for addition of anticoagulation to antiplatelet therapy in preventing long-term ischemic events after ACS. Further research could clarify whether the use of TG parameters to enable risk stratification of patients at heightened long-term procoagulant risk who may benefit most from dual pathway inhibition.

Lowering Low-Density Lipoprotein Particles in Plasma Using Dextran Sulphate Co-Precipitates Procoagulant Extracellular Vesicles.

Plasma extracellular vesicles (EVs) are lipid membrane vesicles involved in several biological processes including coagulation. Both coagulation and lipid metabolism are strongly associated with cardiovascular events. Lowering very-low- and low-density lipoprotein ((V)LDL) particles via dextran sulphate LDL apheresis also removes coagulation proteins. It remains unknown, however, how coagulation proteins are removed in apheresis. We hypothesize that plasma EVs that contain high levels of coagulation proteins are concomitantly removed with (V)LDL particles by dextran sulphate apheresis. For this, we precipitated (V)LDL particles from human plasma with dextran sulphate and analyzed the abundance of coagulation proteins and EVs in the precipitate. Coagulation pathway proteins, as demonstrated by proteomics and a bead-based immunoassay, were over-represented in the (V)LDL precipitate. In this precipitate, both bilayer EVs and monolayer (V)LDL particles were observed by electron microscopy. Separation of EVs from (V)LDL particles using density gradient centrifugation revealed that almost all coagulation proteins were present in the EVs and not in the (V)LDL particles. These EVs also showed a strong procoagulant activity. Our study suggests that dextran sulphate used in LDL apheresis may remove procoagulant EVs concomitantly with (V)LDL particles, leading to a loss of coagulation proteins from the blood.

A novel multiplexed immunoassay identifies CEA, IL-8 and prolactin as prospective markers for Dukes' stages A-D colorectal cancers.

BACKGROUND: Current methods widely deployed for colorectal cancers (CRC) screening lack the necessary sensitivity and specificity required for population-based early disease detection. Cancer-specific protein biomarkers are thought to be produced either by the tumor itself or other tissues in response to the presence of cancers or associated conditions. Equally, known examples of cancer protein biomarkers (e.g., PSA, CA125, CA19-9, CEA, AFP) are frequently found in plasma at very low concentration (pg/mL-ng/mL). New sensitive and specific assays are therefore urgently required to detect the disease at an early stage when prognosis is good following surgical resection. This study was designed to meet the longstanding unmet clinical need for earlier CRC detection by measuring plasma candidate biomarkers of cancer onset and progression in a clinical stage-specific manner. EDTA plasma samples (1 µL) obtained from 75 patients with Dukes' staged CRC or unaffected controls (age and sex matched with stringent inclusion/exclusion criteria) were assayed for expression of 92 human proteins employing the Proseek® Multiplex Oncology I proximity extension assay. An identical set of plasma samples were analyzed utilizing the Bio-Plex Pro™ human cytokine 27-plex immunoassay. RESULTS: Similar quantitative expression patterns for 13 plasma antigens common to both platforms endorsed the potential efficacy of Proseek as an immune-based multiplex assay for proteomic biomarker research. Proseek found that expression of Carcinoembryonic Antigen (CEA), IL-8 and prolactin are significantly correlated with CRC stage. CONCLUSIONS: CEA, IL-8 and prolactin expression were found to identify between control (unaffected), non-malignant (Dukes' A + B) and malignant (Dukes' C + D) stages.

Ultradepletion of human plasma using chicken antibodies: a proof of concept study.

Human plasma arguably represents the most comprehensive version of the human proteome. Despite its immense theoretical discovery potential, plasma has many high and medium abundance proteins that mask low abundance protein disease biomarkers of relevance, making the discovery of novel diagnostic markers particularly difficult. Some form of protein depletion and/or fractionation is essential in order to detect markers of low abundance. Here, we describe a "proof of concept" two-pronged approach to immunodeplete abundant proteins from human plasma. The method, called API (Abundant Protein Immunodepletion), involves the fractionation of plasma using dual ion exchange columns (protein repetitive orthogonal offline fractionation (PROOF)) to simplify the proteome, the production of polyclonal IgY against each fraction and finally using the purified antibodies in a immunodepletion column. We explored the use of this product for immunodepletion of human plasma and identified a total of 165 nonredundant proteins after depletion. Of these, 38 proteins that were not previously identified in nondepleted plasma were now detected. It is envisaged that further optimization of the method as well as its cyclic implementation (by reinjecting depleted plasma into chickens for second round of antibody production) can make this technology highly robust, extremely cost-effective, and ideal for high throughput biomarker discovery.

Targeted Plasma Metabolomics Reveals Association of Acute Myocardial Infarction Risk with the Dynamic Balance between Trimethylamine-N-oxide, Betaine, and Choline.

The relationship between trimethylamine-N-oxide (TMAO), betaine, and choline with acute myocardial infarction (AMI) end point remains unclear. We analyzed plasma TMAO, betaine, and choline concentrations in AMI cases and non-AMI community-dwelling controls by LC-MS/MS to understand how the balance between these metabolites helps to reduce AMI risk. Results showed that the odds ratio (OR) for the highest versus lowest quartiles of betaine was 0.30 (95% CI, 0.10-0.82) after adjustment for AMI risk factors, and the unadjusted OR for quartile 3 versus quartile 1 of TMAO was 2.47 (95% CI, 1.02-6.17) (p < 0.05). The study populations with "high betaine + low TMAO" had a significant protective effect concerning AMI with a multivariable-adjusted OR of 0.20 (95% CI, 0.07-0.55) (p < 0.01). Multivariate linear regression showed that the chronological age was correlated with TMAO concentrations among AMI patients (95% CI, 0.05-3.24, p < 0.01) but not among the controls. This implies a further potential interplay between age and metabolite combination─AMI risk association.

Plasma metallomics reveals potential biomarkers and insights into the ambivalent associations of elements with acute myocardial infarction.

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Using a validated and efficient ICP-MS/MS-based workflow, a total of 30 metallomic features were profiled in a study comprising 101 AMI patients and 66 age-matched healthy controls. The metallomic features include 12 essential elements (Ca, Co, Cu, Fe, K, Mg, Mn, Na, P, S, Se, Zn), 8 non-essential/toxic elements (Al, As, Ba, Cd, Cr, Ni, Rb, Sr, U, V), and 10 clinically relevant element-pair product/ratios (Ca/Mg, Ca×P, Cu/Se, Cu/Zn, Fe/Cu, P/Mg, Na/K, Zn/Se). Preliminary linear regression with feature selection confirmed smoking status as a predominant determinant for the non-essential/toxic elements, and revealed potential routes of action. Univariate assessments with adjustments for covariates revealed insights into the ambivalent relationships of Cu, Fe, and P with AMI, while also confirming cardioprotective associations of Se. Also, beyond their roles as risk factors, Cu and Se may be involved in the response mechanism in AMI onset/intervention, as demonstrated via longitudinal data analysis with 2 additional time-points (1-/6-month follow-up). Finally, based on both univariate tests and multivariate classification modelling, potentially more sensitive markers measured as element-pair ratios were identified (e.g., Cu/Se, Fe/Cu). Overall, metallomics-based biomarkers may have utility for AMI prediction.

An integrated signature of extracellular matrix proteins and a diastolic function imaging parameter predicts post-MI long-term outcomes.

Background: Patients suffering from acute myocardial infarction (AMI) are at risk of secondary outcomes including major adverse cardiovascular events (MACE) and heart failure (HF). Comprehensive molecular phenotyping and cardiac imaging during the post-discharge time window may provide cues for risk stratification for the outcomes. Materials and methods: In a prospective AMI cohort in New Zealand (N = 464), we measured plasma proteins and lipids 30 days after hospital discharge and inferred a unified partial correlation network with echocardiographic variables and established clinical biomarkers (creatinine, c-reactive protein, cardiac troponin I and natriuretic peptides). Using a network-based data integration approach (iOmicsPASS+), we identified predictive signatures of long-term secondary outcomes based on plasma protein, lipid, imaging markers and clinical biomarkers and assessed the prognostic potential in an independent cohort from Singapore (N = 190). Results: The post-discharge levels of plasma proteins and lipids showed strong correlations within each molecular type, reflecting concerted homeostatic regulation after primary MI events. However, the two molecular types were largely independent with distinct correlation structures with established prognostic imaging parameters and clinical biomarkers. To deal with massively correlated predictive features, we used iOmicsPASS + to identify subnetwork signatures of 211 and 189 data features (nodes) predictive of MACE and HF events, respectively (160 overlapping). The predictive features were primarily imaging parameters, including left ventricular and atrial parameters, tissue Doppler parameters, and proteins involved in extracellular matrix (ECM) organization, cell differentiation, chemotaxis, and inflammation. The network signatures contained plasma protein pairs with area-under-the-curve (AUC) values up to 0.74 for HF prediction in the validation cohort, but the pair of NT-proBNP and fibulin-3 (EFEMP1) was the best predictor (AUC = 0.80). This suggests that there were a handful of plasma proteins with mechanistic and functional roles in predisposing patients to the secondary outcomes, although they may be weaker prognostic markers than natriuretic peptides individually. Among those, the diastolic function parameter (E/e' - an indicator of left ventricular filling pressure) and two ECM proteins, EFEMP1 and follistatin-like 3 (FSTL3) showed comparable performance to NT-proBNP and outperformed left ventricular measures as benchmark prognostic factors for post-MI HF. Conclusion: Post-discharge levels of E/e', EFEMP1 and FSTL3 are promising complementary markers of secondary adverse outcomes in AMI patients.

Chicken immune responses to variations in human plasma protein ratios: a rationale for polyclonal IgY ultraimmunodepletion.

Chicken IgY responses against mixtures of six high abundance human plasma proteins were studied across a range of abundances from 1:1 for all six proteins to where one protein predominated above the other five by ≤1000 fold. The ability of any protein in that mixture to mount an IgY response varied. In the 1:1 mixture, human IgG produced the highest and α(1)antitrypsin the lowest individual responses. However, increasing relative abundance of any protein over others increased the total IgY response (i.e., sum of all responses to each antigen) above those obtained for 1:1 ratios. Increasing relative abundance of any protein over others in the mixture (e.g., 1:10, 1:100 and 1:1000) resulted in variations in response to both the overexpressed antigen and to the other five "constant" proteins. The overriding trends were that as individual proteins became relatively more abundant, they elicited higher IgY responses, while the remaining proteins elicited constant or even decreased responses. This study demonstrates that the ability to mount an IgY response to complex plasma protein antigens (e.g., human plasma) is conclusively driven by a combination of individual antigen immunogenicity and the relative abundance of components within any mixture.

Enhanced Thrombin Generation Is Associated with Worse Left Ventricular Scarring after ST-Segment Elevation Myocardial Infarction: A Cohort Study.

Acute myocardial infarction (AMI) is associated with heightened thrombin generation. There are limited data relating to thrombin generation and left ventricular (LV) scarring and LV dilatation in post-MI LV remodeling. We studied 113 patients with ST-segment elevation myocardial infarction (STEMI) who had undergone primary percutaneous coronary intervention (PPCI) (n = 76) or pharmaco-invasive management (thrombolysis followed by early PCI, n = 37). Endogenous thrombin potential (ETP) was measured at baseline, 1 month and 6 months. Cardiovascular magnetic resonance imaging was performed at baseline and 6 months post-MI. Outcomes studied were an increase in scar change, which was defined as an increase in left ventricular infarct size of any magnitude detected by late gadolinium enhancement, adverse LV remodeling, defined as dilatation (increase) of left ventricular end-diastolic volume (LVEDV) by more than 20% and an increase in left ventricular ejection fraction (LVEF). The mean age was 55.19 ± 8.25 years and 91.2% were men. The baseline ETP was similar in the PPCI and pharmaco-invasive groups (1400.3 nM.min vs. 1334.1 nM.min, p = 0.473). Each 10-unit increase in baseline ETP was associated with a larger scar size (adjusted OR 1.020, 95% CI 1.002-1.037, p = 0.027). Baseline ETP was not associated with adverse LV remodeling or an increase in LVEF. There was no difference in scar size or adverse LV remodeling among patients undergoing PPCI vs. pharmaco-invasive management or patients receiving ticagrelor vs. clopidogrel. Enhanced thrombin generation after STEMI is associated with a subsequent increase in myocardial scarring but not LV dilatation or an increase in LVEF at 6 months post-MI.

Plasma tissue factor coagulation activity in post-acute myocardial infarction patients.

Introduction: Coagulation is involved in fibroproliferative responses following acute myocardial infarction (AMI). Left ventricular (LV) remodeling following AMI is closely associated with progression to heart failure. This study aims to assess the association between plasma tissue factor activity and LV remodeling in post-AMI patients. Methods: We studied 228 patients with AMI and 57 healthy subjects. Patients with AMI were categorized into two age- and sex-matched groups: patients with adverse LV remodeling or reverse LV remodeling, defined by an increase or decrease, respectively, in LV end systolic volume by ≥15% over 6 months. TF activity was measured in plasma collected at baseline (within 72 hours of revascularization), 1 month and 6 months post-AMI. Multiple level longitudinal data analysis with structural equation (ML-SEM) model was used to assess the impact of various clinical variables on TF activity in post-AMI. Results: Plasma TF activity in post-AMI patients at baseline (29.05 ± 10.75 pM) was similar to that in healthy subjects but fell at 1 month (21.78 ± 8.23, p<0.001) with partial recovery by 6 months (25.84 ± 8.80, p<0.001) after AMI. Plasma TF activity at 6 month post-AMI was better restored in patients with reverse LV remodeling than those with adverse LV remodeling (27.35 ± 7.14 vs 24.34 ± 9.99; p=0.009) independent of gender, age and relevant cardiovascular risk factors. Conclusions: Plasma TF activity decreased after AMI but was better restored at 6 months in patients with reverse LV remodeling. The clinical significance of changes in post-AMI plasma TF activity needs further investigation.

Multi-Omics Investigation into Acute Myocardial Infarction: An Integrative Method Revealing Interconnections amongst the Metabolome, Lipidome, Glycome, and Metallome.

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. This work aims to investigate the translational potential of a multi-omics study (comprising metabolomics, lipidomics, glycomics, and metallomics) in revealing biomechanistic insights into AMI. Following the N-glycomics and metallomics studies performed by our group previously, untargeted metabolomic and lipidomic profiles were generated and analysed in this work via the use of a simultaneous metabolite/lipid extraction and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis workflow. The workflow was applied to blood plasma samples from AMI cases (n = 101) and age-matched healthy controls (n = 66). The annotated metabolomic (number of features, n = 27) and lipidomic (n = 48) profiles, along with the glycomic (n = 37) and metallomic (n = 30) profiles of the same set of AMI and healthy samples were integrated and analysed. The integration method used here works by identifying a linear combination of maximally correlated features across the four omics datasets, via utilising both block-partial least squares-discriminant analysis (block-PLS-DA) based on sparse generalised canonical correlation analysis. Based on the multi-omics mapping of biomolecular interconnections, several postulations were derived. These include the potential roles of glycerophospholipids in N-glycan-modulated immunoregulatory effects, as well as the augmentation of the importance of Ca-ATPases in cardiovascular conditions, while also suggesting contributions of phosphatidylethanolamine in their functions. Moreover, it was shown that combining the four omics datasets synergistically enhanced the classifier performance in discriminating between AMI and healthy subjects. Fresh and intriguing insights into AMI, otherwise undetected via single-omics analysis, were revealed in this multi-omics study. Taken together, we provide evidence that a multi-omics strategy may synergistically reinforce and enhance our understanding of diseases.

Trans-interaction of risk loci 6p24.1 and 10q11.21 is associated with endothelial damage in coronary artery disease.

BACKGROUND AND AIMS: Single nucleotide polymorphism rs6903956 has been identified as one of the genetic risk factors for coronary artery disease (CAD). However, rs6903956 lies in a non-coding locus on chromosome 6p24.1. We aim to interrogate the molecular basis of 6p24.1 containing rs6903956 risk alleles in endothelial disease biology. METHODS AND RESULTS: We generated induced pluripotent stem cells (iPSCs) from CAD patients (AA risk genotype at rs6903956) and non-CAD subjects (GG non-risk genotype at rs6903956). CRISPR-Cas9-based deletions (Δ63-89bp) on 6p24.1, including both rs6903956 and a short tandem repeat variant rs140361069 in linkage disequilibrium, were performed to generate isogenic iPSC-derived endothelial cells. Edited CAD endothelial cells, with removal of 'A' risk alleles, exhibited a global transcriptional downregulation of pathways relating to abnormal vascular physiology and activated endothelial processes. A CXC chemokine ligand on chromosome 10q11.21, CXCL12, was uncovered as a potential effector gene in CAD endothelial cells. Underlying this effect was the preferential inter-chromosomal interaction of 6p24.1 risk locus to a weak promoter of CXCL12, confirmed by chromatin conformation capture assays on our iPSC-derived endothelial cells. Functionally, risk genotypes AA/AG at rs6903956 were associated significantly with elevated levels of circulating damaged endothelial cells in CAD patients. Circulating endothelial cells isolated from patients with risk genotypes AA/AG were also found to have 10 folds higher CXCL12 transcript copies/cell than those with non-risk genotype GG. CONCLUSIONS: Our study reveals the trans-acting impact of 6p24.1 with another CAD locus on 10q11.21 and is associated with intensified endothelial injury.

Deletion of Mfsd2b impairs thrombotic functions of platelets.

We recently discovered that Mfsd2b, which is the S1P exporter found in blood cells. Here, we report that Mfsd2b is critical for the release of all S1P species in both resting and activated platelets. We show that resting platelets store S1P in the cytoplasm. After activation, this S1P pool is delivered to the plasma membrane, where Mfsd2b is predominantly localized for export. Employing knockout mice of Mfsd2b, we reveal that platelets contribute a minor amount of plasma S1P. Nevertheless, Mfsd2b deletion in whole body or platelets impairs platelet morphology and functions. In particular, Mfsd2b knockout mice show significantly reduced thrombus formation. We show that loss of Mfsd2b affects intrinsic platelet functions as part of remarkable sphingolipid accumulation. These findings indicate that accumulation of sphingolipids including S1P by deletion of Mfsd2b strongly impairs platelet functions, which suggests that the transporter may be a target for the prevention of thrombotic disorders.